- Add comprehensive test coverage for FormTextarea and FormSelect components to validate rendering, accessibility, props forwarding, error handling, and behavior.
- Introduced function-scoped fixtures in e2e tests to ensure test isolation and address event loop issues with pytest-asyncio and SQLAlchemy.
Added comprehensive unit and API tests to validate AgentType category and display fields:
- Category validation for valid, null, and invalid values
- Icon, color, and sort_order field constraints
- Typical tasks and collaboration hints handling (stripping, removing empty strings, normalization)
- New API tests for field creation, filtering, updating, and grouping
Bug Fixes:
- Remove singleton pattern from consolidation/reflection services to
prevent stale database session bugs (session is now passed per-request)
- Add LRU eviction to MemoryToolService._working dict (max 1000 sessions)
to prevent unbounded memory growth
- Replace O(n) list.remove() with O(1) OrderedDict.move_to_end() in
RetrievalCache for better performance under load
- Use deque with maxlen for metrics histograms to prevent unbounded
memory growth (circular buffer with 10k max samples)
- Use full UUID for checkpoint IDs instead of 8-char prefix to avoid
collision risk at scale (birthday paradox at ~50k checkpoints)
Test Updates:
- Update checkpoint test to expect 36-char UUID
- Update reflection singleton tests to expect new factory behavior
- Add reset_memory_reflection() no-op for backwards compatibility
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Adjusted TTL durations and sleep intervals across memory and cache tests for consistent expiration behavior.
- Prevented test flakiness caused by timing discrepancies in token expiration and cache cleanup.
- Add threading.Lock with double-check locking to ScopeManager
- Add asyncio.Lock with double-check locking to MemoryReflection
- Make reset_memory_metrics async with proper locking
- Update test fixtures to handle async reset functions
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Moved tests/unit/models/memory/ to tests/models/memory/ to avoid
Python import path conflicts when pytest collects all tests.
The conflict was caused by tests/models/ and tests/unit/models/ both
having __init__.py files, causing Python to confuse app.models.memory
imports.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added `memory_consolidation` to the task list and updated `__all__` in test files.
- Updated `source_episode_ids` in `Fact` model to use JSON for cross-database compatibility.
- Revised related database migrations to use JSONB instead of ARRAY.
- Adjusted test concurrency in Makefile for improved test performance.
Auto-fixed linting errors and formatting issues:
- Removed unused imports (F401): pytest, Any, AnalysisType, MemoryType, OutcomeType
- Removed unused variable (F841): hooks variable in test
- Applied consistent formatting across memory service and test files
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add comprehensive caching layer for the Agent Memory System:
- HotMemoryCache: LRU cache for frequently accessed memories
- Python 3.12 type parameter syntax
- Thread-safe operations with RLock
- TTL-based expiration
- Access count tracking for hot memory identification
- Scoped invalidation by type, scope, or pattern
- EmbeddingCache: Cache embeddings by content hash
- Content-hash based deduplication
- Optional Redis backing for persistence
- LRU eviction with configurable max size
- CachedEmbeddingGenerator wrapper for transparent caching
- CacheManager: Unified cache management
- Coordinates hot cache, embedding cache, and retrieval cache
- Centralized invalidation across all caches
- Aggregated statistics and hit rate tracking
- Automatic cleanup scheduling
- Cache warmup support
Performance targets:
- Cache hit rate > 80% for hot memories
- Cache operations < 1ms (memory), < 5ms (Redis)
83 new tests with comprehensive coverage.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add MCP-compatible tools that expose memory operations to agents:
Tools implemented:
- remember: Store data in working, episodic, semantic, or procedural memory
- recall: Retrieve memories by query across multiple memory types
- forget: Delete specific keys or bulk delete by pattern
- reflect: Analyze patterns in recent episodes (success/failure factors)
- get_memory_stats: Return usage statistics and breakdowns
- search_procedures: Find procedures matching trigger patterns
- record_outcome: Record task outcomes and update procedure success rates
Key components:
- tools.py: Pydantic schemas for tool argument validation with comprehensive
field constraints (importance 0-1, TTL limits, limit ranges)
- service.py: MemoryToolService coordinating memory type operations with
proper scoping via ToolContext (project_id, agent_instance_id, session_id)
- Lazy initialization of memory services (WorkingMemory, EpisodicMemory,
SemanticMemory, ProceduralMemory)
Test coverage:
- 60 tests covering tool definitions, argument validation, and service
execution paths
- Mock-based tests for all memory type interactions
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add MemoryConsolidationService with Working→Episodic→Semantic/Procedural transfer
- Add Celery tasks for session and nightly consolidation
- Implement memory pruning with importance-based retention
- Add comprehensive test suite (32 tests)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add comprehensive indexing and retrieval system for memory search:
- VectorIndex for semantic similarity search using cosine similarity
- TemporalIndex for time-based queries with range and recency support
- EntityIndex for entity-based lookups with multi-entity intersection
- OutcomeIndex for success/failure filtering on episodes
- MemoryIndexer as unified interface for all index types
- RetrievalEngine with hybrid search combining all indices
- RelevanceScorer for multi-signal relevance scoring
- RetrievalCache for LRU caching of search results
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add scope management system for hierarchical memory access:
- ScopeManager with hierarchy: Global → Project → Agent Type → Agent Instance → Session
- ScopePolicy for access control (read, write, inherit permissions)
- ScopeResolver for resolving queries across scope hierarchies with inheritance
- ScopeFilter for filtering scopes by type, project, or agent
- Access control enforcement with parent scope visibility
- Deduplication support during resolution across scopes
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements procedural memory for learned skills and procedures:
Core functionality:
- ProceduralMemory class for procedure storage/retrieval
- record_procedure with duplicate detection and step merging
- find_matching for context-based procedure search
- record_outcome for success/failure tracking
- get_best_procedure for finding highest success rate
- update_steps for procedure refinement
Supporting modules:
- ProcedureMatcher: Keyword-based procedure matching
- MatchResult/MatchContext: Matching result types
- Success rate weighting in match scoring
Test coverage:
- 43 unit tests covering all modules
- matching.py: 97% coverage
- memory.py: 86% coverage
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements the episodic memory service for storing and retrieving
agent task execution experiences. This enables learning from past
successes and failures.
Components:
- EpisodicMemory: Main service class combining recording and retrieval
- EpisodeRecorder: Handles episode creation, importance scoring
- EpisodeRetriever: Multiple retrieval strategies (recency, semantic,
outcome, importance, task type)
Key features:
- Records task completions with context, actions, outcomes
- Calculates importance scores based on outcome, duration, lessons
- Semantic search with fallback to recency when embeddings unavailable
- Full CRUD operations with statistics and summarization
- Comprehensive unit tests (50 tests, all passing)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements session-scoped ephemeral memory with:
Storage Backends:
- InMemoryStorage: Thread-safe fallback with TTL support and capacity limits
- RedisStorage: Primary storage with connection pooling and JSON serialization
- Auto-fallback from Redis to in-memory when unavailable
WorkingMemory Class:
- Key-value storage with TTL and reserved key protection
- Task state tracking with progress updates
- Scratchpad for reasoning steps with timestamps
- Checkpoint/snapshot support for recovery
- Factory methods for auto-configured storage
Tests:
- 55 unit tests covering all functionality
- Tests for basic ops, TTL, capacity, concurrency
- Tests for task state, scratchpad, checkpoints
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements Sub-Issue #87 of Issue #62 (Agent Memory System).
Core infrastructure:
- memory/types.py: Type definitions for all memory types (Working, Episodic,
Semantic, Procedural) with enums for MemoryType, ScopeLevel, Outcome
- memory/config.py: MemorySettings with MEM_ env prefix, thread-safe singleton
- memory/exceptions.py: Comprehensive exception hierarchy for memory operations
- memory/manager.py: MemoryManager facade with placeholder methods
Directory structure:
- working/: Working memory (Redis/in-memory) - to be implemented in #89
- episodic/: Episodic memory (experiences) - to be implemented in #90
- semantic/: Semantic memory (facts) - to be implemented in #91
- procedural/: Procedural memory (skills) - to be implemented in #92
- scoping/: Scope management - to be implemented in #93
- indexing/: Vector indexing - to be implemented in #94
- consolidation/: Memory consolidation - to be implemented in #95
Tests: 71 unit tests for config, types, and exceptions
Docs: Comprehensive implementation plan at docs/architecture/memory-system-plan.md
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added detailed unit tests for `/context` endpoints, covering health checks, context assembly, token counting, budget retrieval, and cache invalidation.
- Included edge cases, error handling, and input validation for context-related operations.
- Improved test coverage for the Context Management module with mocked dependencies and integration scenarios.
- Introduced end-to-end tests for MCP workflows, including server discovery, authentication, context engine operations, error handling, and input validation.
- Added full lifecycle tests for agent workflows, covering type management, instance spawning, status transitions, and admin-only operations.
- Enhanced test coverage for real-world MCP and Agent scenarios across PostgreSQL and async environments.
- Introduced integration tests covering backend, LLM Gateway, Knowledge Base, and Context Engine.
- Includes health checks, tool listing, token counting, and end-to-end MCP flows.
- Added `RUN_INTEGRATION_TESTS` environment flag to enable selective test execution.
- Includes a quick health check script to verify service availability before running tests.
- Added timeout enforcement for token counting, scoring, and compression with detailed error handling.
- Introduced tenant isolation in context caching using project and agent identifiers.
- Enhanced budget management with stricter checks for critical context overspending and buffer limitations.
- Optimized per-context locking with cleanup to prevent memory leaks in concurrent environments.
- Updated default assembly timeout settings for improved performance and reliability.
- Improved XML escaping in Claude adapter for safety against injection attacks.
- Standardized token estimation using model-specific ratios.
- Cleaned up unnecessary comments in `__all__` definitions for better readability.
- Adjusted indentation and formatting across modules for improved clarity (e.g., long lines, logical grouping).
- Simplified conditional expressions and inline comments for context scoring and ranking.
- Replaced some hard-coded values with type-safe annotations (e.g., `ClassVar`).
- Removed unused imports and ensured consistent usage across test files.
- Updated `test_score_not_cached_on_context` to clarify caching behavior.
- Improved truncation strategy logic and marker handling.
- Add tests for truncation edge cases, including zero tokens, short content, and marker handling.
- Add concurrency tests for scoring to verify per-context locking and handling of multiple contexts.
Phase 7 of Context Management Engine - Main Engine:
- Add ContextEngine as main orchestration class
- Integrate all components: calculator, scorer, ranker, compressor, cache
- Add high-level assemble_context() API with:
- System prompt support
- Task description support
- Knowledge Base integration via MCP
- Conversation history conversion
- Tool results conversion
- Custom contexts support
- Add helper methods:
- get_budget_for_model()
- count_tokens() with caching
- invalidate_cache()
- get_stats()
- Add create_context_engine() factory function
Tests: 26 new tests, 311 total context tests passing
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Phase 5 of Context Management Engine - Model Adapters:
- Add ModelAdapter abstract base class with model matching
- Add DefaultAdapter for unknown models (plain text)
- Add ClaudeAdapter with XML-based formatting:
- <system_instructions> for system context
- <reference_documents>/<document> for knowledge
- <conversation_history>/<message> for chat
- <tool_results>/<tool_result> for tool outputs
- XML escaping for special characters
- Add OpenAIAdapter with markdown formatting:
- ## headers for sections
- ### Source headers for documents
- **ROLE** bold labels for conversation
- Code blocks for tool outputs
- Add get_adapter() factory function for model selection
Tests: 33 new tests, 256 total context tests passing
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add TokenCalculator with LLM Gateway integration for accurate token
counting with in-memory caching and fallback character-based estimation.
Implement TokenBudget for tracking allocations per context type with
budget enforcement, and BudgetAllocator for creating budgets based on
model context window sizes.
- TokenCalculator: MCP integration, caching, model-specific ratios
- TokenBudget: allocation tracking, can_fit/allocate/deallocate/reset
- BudgetAllocator: model context sizes, budget creation and adjustment
- 35 comprehensive tests covering all budget functionality
Part of #61 - Context Management Engine
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added `record_action` in `RateLimiter` for precise tracking of slot consumption post-validation.
- Introduced deduplication mechanism for warning alerts in `CostController` to prevent spamming.
- Refactored `CostController`'s session and daily budget alert handling for improved clarity.
- Implemented test suites for `CostController` and `SafetyGuardian` to validate changes.
- Expanded integration testing to cover deduplication, validation, and loop detection edge cases.
Improved code readability and uniformity by standardizing line breaks, indentation, and inline conditions across safety-related services, models, and tests, including content filters, validation rules, and emergency controls.
The delay2 and delay3 variables were calculated but never asserted,
causing lint warnings. Added assertions to verify all delays are
positive and within max bounds.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Core MCP client implementation with comprehensive tooling:
**Services:**
- MCPClientManager: Main facade for all MCP operations
- MCPServerRegistry: Thread-safe singleton for server configs
- ConnectionPool: Connection pooling with auto-reconnection
- ToolRouter: Automatic tool routing with circuit breaker
- AsyncCircuitBreaker: Custom async-compatible circuit breaker
**Configuration:**
- YAML-based config with Pydantic models
- Environment variable expansion support
- Transport types: HTTP, SSE, STDIO
**API Endpoints:**
- GET /mcp/servers - List all MCP servers
- GET /mcp/servers/{name}/tools - List server tools
- GET /mcp/tools - List all tools from all servers
- GET /mcp/health - Health check all servers
- POST /mcp/call - Execute tool (admin only)
- GET /mcp/circuit-breakers - Circuit breaker status
- POST /mcp/circuit-breakers/{name}/reset - Reset circuit breaker
- POST /mcp/servers/{name}/reconnect - Force reconnection
**Testing:**
- 156 unit tests with comprehensive coverage
- Tests for all services, routes, and error handling
- Proper mocking and async test support
**Documentation:**
- MCP_CLIENT.md with usage examples
- Phase 2+ workflow documentation
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added tests for OAuth provider admin and consent endpoints covering edge cases.
- Extended agent-related tests to handle incorrect project associations and lifecycle state transitions.
- Introduced tests for sprint status transitions and validation checks.
- Improved multiline formatting consistency across all test functions.
Bug Fixes:
- bulk_terminate_by_project now unassigns issues before terminating agents
to prevent orphaned issue assignments
- PATCH /issues/{id} now validates sprint status - cannot assign issues
to COMPLETED or CANCELLED sprints
- archive_project now performs cascading cleanup:
- Terminates all active agent instances
- Cancels all planned/active sprints
- Unassigns issues from terminated agents
Added edge case tests for all fixed bugs (19 new tests total):
- TestBulkTerminateEdgeCases
- TestSprintStatusValidation
- TestArchiveProjectCleanup
- TestDataIntegrityEdgeCases (IDOR protection)
Coverage: 93% (1836 tests passing)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit fixes 4 production bugs found via edge case testing:
1. BUG: System allowed assigning issues to terminated agents
- Added validation in issue creation endpoint
- Added validation in issue update endpoint
- Added validation in issue assign endpoint
2. BUG: Issues remained orphaned when agent was terminated
- Agent termination now auto-unassigns all issues from that agent
These bugs could lead to issues being assigned to non-functional agents
that would never work on them, causing work to stall silently.
Tests added in tests/api/routes/syndarix/test_edge_cases.py to verify:
- Cannot assign issue to terminated agent (3 variations)
- Issues are auto-unassigned when agent is terminated
- Various other edge cases (sprints, projects, IDOR protection)
Coverage: 88% → 93% (1830 tests passing)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add 22 tests for agents API covering:
- CRUD operations (spawn, list, get, update, delete)
- Lifecycle management (pause, resume)
- Agent metrics (single and project-level)
- Authorization and access control
- Status filtering
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add 24 tests for issues API covering:
- CRUD operations (create, list, get, update, delete)
- Status and priority filtering
- Search functionality
- Issue statistics
- Authorization and access control
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
